Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Strands Decider is a compact and swift decision-making model, known as a System One model, tailored for agentic AI applications. In contrast to a language model that produces random text, this model selects from a set of predefined options, responds to yes-or-no inquiries, or assesses inputs using an ordered scale. Each decision made by the Strands Decider is accompanied by a calibrated confidence score, enabling the efficient processing of routine decisions while allowing uncertain cases to be escalated to either a larger model or a human for further analysis. The initial iteration of this model, strands-decider-2B, comprises 1.9 billion parameters and is built upon the Qwen3.5-2B-Base architecture, featuring a streamlined pointer head in place of its language-modeling component. It performs evaluations in a single forward pass, eliminating the need for text generation or a decoding loop. Supported types of decisions encompass choice selections, noul for probability assessments, and score for evaluating ordered scales. This model is engineered for a variety of applications, including model routing, selecting tools, verifying tool arguments, triaging requests, establishing grounding and safety measures, classifying policies, and providing economical evaluations, thereby enhancing its utility in diverse AI workflows.
Description
Vectara offers LLM-powered search as-a-service. The platform offers a complete ML search process, from extraction and indexing to retrieval and re-ranking as well as calibration. API-addressable for every element of the platform. Developers can embed the most advanced NLP model for site and app search in minutes.
Vectara automatically extracts text form PDF and Office to JSON HTML XML CommonMark, and many other formats. Use cutting-edge zero-shot models that use deep neural networks to understand language to encode at scale. Segment data into any number indexes that store vector encodings optimized to low latency and high recall. Use cutting-edge, zero shot neural network models to recall candidate results from millions upon millions of documents. Cross-attentional neural networks can increase the precision of retrieved answers. They can merge and reorder results. Focus on the likelihood that the retrieved answer is a probable answer to your query.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Datavolo
No
IBM watsonx.data
No
Langflow
No
Model Context Protocol (MCP)
No
Strands Agents
Yes
Integrations
Datavolo
Yes
IBM watsonx.data
Yes
Langflow
Yes
Model Context Protocol (MCP)
Yes
Strands Agents
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Strands Labs
Country
United States
Website
github.com/strands-labs/strands-decider
Vendor Details
Company Name
Vectara
Founded
2020
Country
United States
Website
vectara.com
Product Features
Product Features
Enterprise Search
AI / Machine Learning
No
Faceted Search / Filtering
No
Full Text Search
No
Fuzzy Search
No
Indexing
No
Text Analytics
No
eDiscovery
No